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Persistent Cognitive Dysfunction Despite Clinical Improvement in Schizophrenia

2011· review· en· W2325986640 on OpenAlexaff
Amresh Shrivastava, Megan Johnston, Nilesh Shah, Meghana Thakar, Larry Stitt

Bibliographic record

VenueJournal of Psychiatric Practice · 2011
Typereview
Languageen
FieldMedicine
TopicSchizophrenia research and treatment
Canadian institutionsWestern UniversityUniversity of TorontoLawson Health Research Institute
Fundersnot available
KeywordsSchizophrenia (object-oriented programming)Cognitive remediation therapyCognitionCognitive skillEffects of sleep deprivation on cognitive performanceExecutive functionsPsychologyClinical psychologyPsychiatryCognitive neuropsychologyWorking memoryMedicineNeuropsychology

Abstract

fetched live from OpenAlex

One negative outcome associated with schizophrenia is a deterioration of cognitive functioning. Little is known about what happens to cognitive abilities in the years following a diagnosis of first-episode schizophrenia. This study assessed the cognitive functioning of 61 individuals with first-episode schizophrenia who showed significant clinical improvement (Clinical Global Improvement rating of much or very much improved) after 10 years of treatment, comparing their cognitive functioning at the time of the initial diagnosis and at 10-year follow-up. Our results indicated deterioration in some cognitive abilities at baseline with further decline in this area found after 10 years. Visuomotor integration, working memory, and executive functioning deteriorated in the 10 years of treatment following diagnosis, and many individuals who were classified as much or very much improved still demonstrated abnormal cognitive functioning. These findings suggest the need for greater focus on cognitive functioning in treatment for schizophrenia.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.100
GPT teacher head0.430
Teacher spread0.330 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations10
Published2011
Admission routes1
Has abstractyes

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